Project Abstract Motivation: Chronic kidney disease (CKD) affects more than 500 million people. Children commonly develop CKD from urinary obstructive diseases and nephrotoxic therapies, and then suffer severe growth failure, hypertension, cardiovascular risks, and neurocognitive deficits, and eventually end-stage kidney disease. Accurate renal function quantification will improve clinical management of hydronephrosis (1 in 100 babies) and dosing/selection of chemotherapeutic regimens in oncology patients. Glomerular filtration rate (GFR), the biomarker of renal function, is derived from blood or urine tests. These tests only provide global GFR and are limited in accuracy, especially in children, and even more so in children with cancer. MRI offers superb anatomic delineation without ionizing radiation, and is thus ideal for pediatric kidney imaging. However, MRI has not been widely adopted for pediatric renal function evaluation due to lack of reliability and cumbersome workflow. These hurdles stem from the fact that the critical components required for global and regional GFR calculation, including high spatiotemporal resolution, plasma flow and arterial input function, are difficult to obtain, and that accurate image segmentation of kidneys (cortex and medulla) is labor intensive. Additionally, although the same contrast agent injection can be used for obstruction evaluation, certain areas of the kidney suffer from significant signal loss using standard MRI acquisition techniques due to high contrast agent concentrations. This project addresses these major challenges for automated comprehensive renal function evaluation in children. Approach: The project has three development aims, which are validated by clinical studies. Aim 1 will enable novel free-breathing time-resolved 3D dynamic contrast enhanced MRI that simultaneously provides accurate GFR calculation and renal plasma flow. This is achieved by incorporating self-navigated motion compensation, fast acquisition with parallel imaging and compressed sensing, and phase-contrast flow imaging. The second aim is to develop multiple new image analysis methods to extract GFR and renal plasma flow (RPF) that leverage novel flow data of Aim 1, as well as automated new machine-learning image processing techniques for the segmentation of kidneys and ultimately global and regional GFR calculation. In Aim 3, we will develop and integrate ultrashort-echo-time techniques to address the MRI signal loss due to T2* effects from high contrast concentration for patients with obstruction, and further incorporate motion compensation and accelerated imaging methods to enable time-resolved high-resolution dynamic MRI for contrast washout kinetics analysis in the same MR exam. Aim 4 will determine the performance of these methods in a clinical setting. Significance: This work will lead to robust, automated comprehensive pediatric renal MRI for safer and more accurate renal function evaluation in children. The techniques will facilitate widespread application in the com- munity setting and permit robust evaluation of renal function, for both children and adults.